How to Ask for Help from Tableau Support


This post describes an approach to ensure you get the best possible response from Tableau Support, with the fastest possible turn-around time.


After years of working on Enterprise systems I've found that, when I have a problem, the best solution is to solve it myself.

If I cannot solve it myself, then the problem is significant, and I want a valuable answer as quickly as possible.

Problem Definition

Tableau is a complex piece of software. Communication challenges can be among the largest of the hurdles to overcome when working through an issue.

The free text entry box allows unformatted text: no headers, no images. Worse: if my plain text is structured poorly, the Support Engineer may have no choice but to waste valuable time asking me questions.

My Solution

In each new support request, my free text contains one sentence. And there are two attachments.

Dear Tableau Support,

Please review the attached PDF and packaged workbook.

Keith Helfrich
(415) 400-6640


The PDF is a no frills document, which follows a logical structure.

Descriptive text is augmented with screen shots that are marked up with arrows & call-outs.

Not each of these sections is required for every

Dates, Times, and Universal Coordination


This post provides an overview and various methods converting dates between time zones, with examples and considerations for Daylight Savings time.

Having , I was curious to observe that, apparently, the optimal time for me to send tweets is on Mondays at around 2am. But wait. I don't send tweets while I'm sleeping. So, how can this be?

It's because the Twitter Analytics time stamps are stored in UTC.

Store Universally, Display Locally

As a best practice, one should store data in as constistent & portable a format as possible. For date & time values, that format is Coordinated Universal Time.

So we should store our data in UTC and convert it into the local time zone for display. But conversion is tricky: offsetting the hour is easy. It's daylight savings that you need to consider.

Governments the world over are constantly tinkering with daylight savings. Not only national laws, but also state, provencial, and local municipality laws are each constantly changing.

The country of Argentina, for a personal example, attempted twice during my seven years living in Buenos Aires to switch to daylight savings. They

Leverage Dave's Twitter Analytics


This post provides fast & easy steps for leveraging to make it your own. There's a bit of R code, and a repeatable process to update your view with new data as often as you like.

"Stealing like an Artist" is a widely accepted within the Tableau Community. So much so.. the Tableau Public Blog has a post by Hanne Løvik with instructions for how to reverse engineer a dashboard:

Just finishing a bit of burglary myself, I figure the best way to repay the community is to publish my steps. Now you can steal a little bit from both of us.

Let's Make This Quick

1. Download Dave's Workbook

Use the fancy new toolbar on the , and pull Dave's dashboard down to your hard drive.

2. Grab Your Data

From , you could get all the available data at once. But our goal is to build a repeatible pipeline. So let's begin that process now. Download one month at a time, each month to a separate CSV file.

3. Row Bind These Files Together

Here's a screenshot of my directory structure:


Blended Boolean Column Totals are Not What They Seem


Stumped by a blending problem where the column total for a blended calculation was zero, I called on my friend Joe Mako.

Exceptionally generous with his time & knowledge, Joe helped me to understand: what at first had seemed to be a simple confusion was actually various roadblocks in Tableau that each require some effort to understand & work around.

Summarizing the knowledge I received from Joe, I'd like to thank him again for his generosity! All of the packaged workbooks are attached to my forum question, which is here:

Think of Totals as a ~Separate Sheet

The first bit of insight is that column totals can generally be thought of as a semi~separate worksheet. This is especially true for automatic totals.

In many ways, automatic column totals behave like a TOTAL() calculation. That is, they are performed on the server (inside of the data source). And as a result, they explicitly ignore the dimensions on the rows shelf of your worksheet.

This is an important concept, one that plays into the solution and one that Curtis Harris has also hinted at with his clever method for improving

Temp Tables Take Time


In a performance optimized , especially one utilizing and such as Vertica, the creation of temporary tables by a front-end tool like Tableau can be devastating to your response times. Temp tables have long been loathed by the administrators of all database technologies, across the board, for their negative impact on performance. But the situation becomes all the more exceptional in Vertica, precisely because the DBMS is so highly optimized for performance.

In this post I summarize some of my findings with respect to the use of temp tables by Tableau. This information is possibly incomplete or imprescise, and is certain to decay in accuracy over time. Yet the broader strokes & various considerations are ones you can utilize as context for your own investigations.

One of Three Strategies

To make use of the results from earlier queries during blending, grouping, and filtering operations (such as add to context), Tableau will generally choose between one of three strategies. If the first strategy doesn’t work out, then Tableau quickly tries next one. If that fails, then Tableau tries the last one.

Three strategies:

  • temp table in the database
  • sub-query in the database
  • data

Color the Dupes


Not only because it rhymes with my first Tableau post ever, , but also because it's pretty darn cool, here's a post on how to Color Duplicate Records in Tableau.

Even if coloring dupes isn't your top priority, the table calcs / color palette know-how are super useful and they definitely transcend the use case. In fact, stick with me & I'll show you how to assign a distinct color palette to a continuous measure pill. There's juicy insight to be gained by doing so.

My goal was to highlight the strings that appear more than once, each pair with a distinct color. Having trouble with it, I went to the community forums with two problems:

  1. My table calcs worked, but they were kludgy
  2. Since they use aggregations, table calcs are measures
    • and measures can't receive a default color palette that is distinct

Identifying Duplicate Records

My initial approach was over-kill, and I knew it. I was nesting five calcs to identify the dupes & assign them a distinct value for the color. Moreover, I was manipulating strings, which is bad for performance. When computing it's always

Tableau Conference Television

A little scraping, a little reshaping, some janitorial munging.

Some natural language processing, a little blending, insert an image, add a few "popping" dashboard actions, and violá!

Tableau Conference Television:

Big THANKS to all of these folks whose contributions to the Tableau Community know-how have been incorporated into this vis.

keyword intersection logic (Johathan Drummey)

sheet popping (Matthew Lutton, Joe Oppelt, Ryan Sleeper)

golden ratio (Ryan Sleeper)

making a vis that stops traffic (Anya A'Hearn, Dan Montgomery, Paul Banoub)

unexpected interactivity (Dustin Smith)

So many little details must go into a well designed dashboard..

Word Count: 97

NPR, Oh Data Where Art Thou? Deux.


A second open letter to

Regarding your article titled "No, Seriously, How Contagious Is Ebola?", October 02, I would ask is there not more to this story?

Your article addresses the question, 'should Americans be concerned?' And your conclusion is no, thanks to the country's public health system the Ebola virus is not likely to spread within US borders.

Reporting on a contagion scale, you conclude: Ebola scores a 2, while the Measles is nine times more contagious. "Nothing to worry about here" you report, with prominent info-graphic & supporting technical detail.

And there your analysis stops; satisfied within a very narrow context.

Please contrast your own data journalism and information visualization practices to a similar report from The Washington Post titled, "Ebola spreads slower, kills more than other diseases", By Bonnie Berkowitz and Lazaro Gamio, Published: Oct. 9, 2014.

Reporting on a deadliness scale, The Post finds Ebola to be most lethal; concluding that while more highly contagious virus like Mumps, Chicken Pox, Whooping cough, and Flu infect the unvaccinated more rapidly: a large majority of their victims recover.

Data journalism communicates

The Anatomy of a Nested Table Calculation


The twittersphere & inter-webs are abuzz with help understanding Tableau Table Calcs. Among the more recent, these are my favorites:

  • Chris Love's in-depth, three part series:
    • , ,
  • Jonathan Drummey's Think Data Thursday:
  • Joe Mako & Matt Lutton breaking it down IRT:

And fully two years ago now, Jonathan started to compile this list of resources for all skill levels:

With such a trove of useful information available, this post of mine is brief & tactical: The Anatomy of a Nested Table Calc, i.e. what does it look like?

Mixing Pigments

If data is our paint, then Table Calcs are the Tableau artist's wooden palette: the place where we can "mix & match our pigments".

For more detail on the difference between Table Calcs & Calculated Fields, see the .

The Nested Table Calc

To annotate the Anatomy of a Nested Table Calc, I'll piggy-back upon the example recently narrated by Joe & Matthew in their 12 minute TRL video .

First, a run-down of

Master Tableau Approach


In an earlier post, titled , I have summarized and added color to a talk by Joe Mako in which he highlighted the advanced concepts that a master practitioner can use to achieve flow by working with instead of against Tableau. This was an excellent talk which he also .

In this new post, Master Tableau Approach, I’ll summarize & add color to a TC14 session from Bethany Lyons and Alan Eldridge, titled Jedi Level Calculation Techniques. Today's topic is the thought process used by a master practitioner when deciding which technique to employ when answering a complex question using Tableau.

How to Think

While introducing his own TC14 session, , Dustin Smith described the Tableau Jedi not as the person who knows every tip and trick. He instead described a Jedi as the person who knows how to best approach the problem.

In a similar vein, Bethany and Alan emphasized during their session that: While every problem on the planet may be solvable with a Table Calc, doing so can prove to be quite painful. The aim of their two hour lab was not to teach